Abstract
<jats:title>Abstract</jats:title> <jats:p>Computational psychiatry leverages tools and frameworks from cognitive neuroscience, computer science, and decision science to investigate mental computations in psychopathology, aiming to uncover complex brain-behavior relationships that traditional methods may overlook. This emerging field encompasses both theory-guided approaches that rely on formal models of cognitive processes and data-driven approaches to forecasting clinical outcomes or detecting patterns in large, complex datasets. This chapter introduces computational psychiatry and explores the largely untapped potential of combining computational methods with transdiagnostic dimensional models of psychopathology. The chapter provides an illustrative example examining how two facets of antagonism are differentially linked to learning signals within the default network that shape reciprocity during a social exchange task. It concludes by addressing three key challenges for integrating computational psychiatry and dimensional models.</jats:p>